Time preferences are reliable across time-horizons and verbal versus experiential tasks

Individual differences in delay-discounting correlate with important real world outcomes, for example education, income, drug use, and criminality. As such, delay-discounting has been extensively studied by economists, psychologists and neuroscientists to reveal its behavioral and biological mechanisms in both human and non-human animal models. However, two major methodological differences hinder comparing results across species. Human studies present long time-horizon options verbally, whereas animal studies employ experiential cues and short delays. To bridge these divides, we developed a novel language-free experiential task inspired by animal decision-making studies. We found that the ranks of subjects' time-preferences were reliable across both verbal/experiential and second/day differences. Yet, discount factors scaled dramatically across the tasks, indicating a strong effect of temporal context. Taken together, this indicates that individuals have a stable, but context-dependent, time-preference that can be reliably assessed using different methods, providing a foundation to bridge studies of time-preferences across species.

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Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11-13% of the variance in educational attainment and 7-10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research.

Genome-wide association study identifies 74 loci associated with educational attainment

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.

Genetic lotteries within families

Drawing on findings from the biomedical literature, this paper introduces the idea that specific exogenously inherited differences in the genetic code between full biological siblings can be used to test within-family estimators and potentially improve our understanding of economic relationships. These points are illustrated with an application to identify the causal impact of several poor health conditions on academic outcomes. We present evidence that family fixed effects estimators by themselves cannot fully account for the endogeneity of poor health when estimating education production functions. Further, our analysis elucidates the situations under which genetic markers can serve as instrumental variables for specific health conditions.

A genetic instrumental variables analysis of the effects of prenatal smoking on birth weight: evidence from two samples

There is a large literature showing the detrimental effects of prenatal smoking on birth and childhood health outcomes. It is somewhat unclear though, whether these effects are causal or reflect other characteristics and choices by mothers who choose to smoke that may also affect child health outcomes or biased reporting of smoking. In this paper we use genetic markers that predict smoking behaviors as instruments to address the endogeneity of smoking choices in the production of birth and childhood health outcomes. Our results indicate that prenatal smoking produces more dramatic declines in birth weight than estimates that ignore the endogeneity of prenatal smoking, which is consistent with previous studies with non-genetic instruments. We use data from two distinct samples from Norway and the United States with different measured instruments and find nearly identical results. The study provides a novel application that can be extended to study several behavioral impacts on health and social and economic outcomes.

The impact of poor health on academic performance: New evidence using genetic markers

This paper examines the influence of health conditions on academic performance during adolescence. To account for the endogeneity of health outcomes and their interactions with risky behaviors we exploit natural variation within a set of genetic markers across individuals. We present evidence that specific genetic markers have good statistical properties to identify the impacts of ADHD, depression and obesity. These markers help reveal a new dynamism from poor health to lower academic achievement with substantial heterogeneity in their impacts across genders. Our investigation further exposes the considerable challenges in identifying health impacts due to the prevalence of comorbid health conditions, with clear implications for the health economics literature.

Worker sorting, compensating differentials and health insurance: evidence from displaced workers

This article introduces an empirical strategy to the compensating differentials literature that (i) allows both individual observed and unobserved characteristics to be rewarded differently in firms based on health insurance provision, and (ii) selection to jobs that provide benefits to operate on both sides of the labor market. Estimates of this model are used to directly test empirical assumptions that are made with popular econometric strategies in the health economics literature. Our estimates reject the assumptions underlying numerous cross sectional and longitudinal estimators. We find that the provision of health insurance has influenced wage inequality. Finally, our results suggest there have been substantial changes in how displaced workers sort to firms that offer health insurance benefits over the past two decades. We discuss the implications of our findings for the compensating differentials literature.